Applied multivariate statistical analysis, Volume 1
This market-leading book offers a readable introduction to the statistical analysis of multivariate observations. Its overarching goal is to provide readers with the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Chapter topics include aspects of multivariate analysis, matrix algebra and random vectors, sample geometry and random sampling, the multivariate normal distribution, inferences about a mean vector, comparisons of several multivariate means, multivariate linear regression models, principal components, factor analysis and inference for structured covariance matrices, canonical correlation analysis, and discrimination and classification. For experimental scientists in a variety of disciplines.
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a very comphrehensive and in-dept monograph, good multivariate statistical handbook for research or grad studies.
Review: Applied Multivariate Statistical AnalysisUser Review - Kevin Zelnio - Goodreads
Used for a graduate level course in Multivariate Statiistics. Was able to follow the text, which was well-organized and had a useful breadth of topics. Read full review
ASPECTS OF MULTIVARIATE ANALYSIS
MATRIX ALGEBRA AND RANDOM VECTORS
SAMPLE GEOMETRY AND RANDOM SAMPLING
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